Due to signal interference and airflow disturbance in gas flow measurement,it cannot meet the precise measurement requirements of industrial fields such as metallurgy,gas,and power genera-tion,a gas flow detection system based on gas flow sensor collection and variational mode decomposi-tion(VMD)filtering optimization prediction compensation was designed.The signal collected by the gas flow sensor was filtered and processed using variational mode decomposition,And use convolutional kernel extreme learning machine(convKELM)prediction model to predict and compensate for data er-rors.The experimental results show that the VMD-ConvKELM method has superior performance in signal decomposition and error prediction compensation tasks.By comparing the prediction accuracy of different algorithms,the results show that the VMD-ConvKELM optimized gas metering detection can effectively measure the actual flow value,with high accuracy and more stable and reliable results.
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